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Cognitive Biases in Software Development


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Cognitive biases are hardwired behaviors that influence developer actions and can set them on an incorrect course of action, necessitating backtracking. Although researchers have found that cognitive biases occur in development tasks in controlled lab studies, we still do not know how these biases affect developers' everyday behavior. Without such an understanding, development tools and practices remain inadequate. To close this gap, we conducted a two-part field study to examine the extent to which cognitive biases occur, the consequences of these biases on developer behavior, and the practices and tools that developers use to deal with these biases. We found about 70% of observed actions were associated with at least one cognitive bias. Even though developers recognized that biases frequently occur, they are forced to deal with such issues with ad hoc processes and suboptimal tool support. As one participant (IP12) lamented: There is no salvation!

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1. Introduction

Cognitive biases are systematic deviations from optimal reasoning17 that influence how we find, evaluate, and remember information. These "shortcuts" to potential solutions can take several forms, and regularly occur in our everyday behavior. For example, confirmation bias (tendency to pay more attention to information that agrees with our preconceptions) is demonstrated in some individuals' characterization of the COVID-19 virus as "just another u," prompting them to engage in social behavior contrary to experts' and health organizations' advice. As with this example, the occurrence of cognitive biases can cause significant impacts on society.

Software developers are not immune from such behavior, and may exhibit biases for several reasons. For example, some biases are a result of attempts to bypass our limited cognitive capacity (for example, availability bias may prompt developers to choose solutions based on examples they readily remember), whereas others are a result of prior experience with a solution (for example, belief perseverance bias may force developers to focus more on the code they believe has the bug), or individual problem-solving styles (for example, hyperbolic discounting bias may encourage developers to choose a solution with smaller and quicker rewards).


 

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